Exhaustive search for conservation networks of populations representing genetic diversity.

Conservation strategies routinely use optimization methods to identify the smallest number of units required to represent a set of features that need to be conserved, including biomes, species, and populations. In this study, we provide R scripts to facilitate exhaustive search for solutions that represent all of the alleles in networks with the smallest possible number of populations. The script also allows other variables to be added to describe the populations, thereby providing the basis for multi-objective optimization and the construction of Pareto curves by averaging the values in the solutions. We applied this algorithm to an empirical dataset that comprised 23 populations of Eugenia dysenterica, which is a tree species with a widespread distribution in the Cerrado biome. We observed that 15 populations would be necessary to represent all 249 alleles based on 11 microsatellite loci, and that the likelihood of representing all of the alleles with random networks is less than 0.0001. We selected the solution (from two with the smallest number of populations) obtained for the populations with a higher level of climatic stability as the best strategy for in situ conservation of genetic diversity of E. dysenterica. The scripts provided in this study are a simple and efficient alternative to more complex optimization methods, especially when the number of populations is relatively small (i.e., <25 populations).

Multi-objective optimization in systematic conservation planning and the representation of genetic variability among populations.

Biodiversity crises have led scientists to develop strategies for achieving conservation goals. The underlying principle of these strategies lies in systematic conservation planning (SCP), in which there are at least 2 conflicting objectives, making it a good candidate for multi-objective optimization. Although SCP is typically applied at the species level (or hierarchically higher), it can be used at lower hierarchical levels, such as using alleles as basic units for analysis, for conservation genetics. Here, we propose a method of SCP using a multi-objective approach. We used non-dominated sorting genetic algorithm II in order to identify the smallest set of local populations of Dipteryx alata (baru) (a Brazilian Cerrado species) for conservation, representing the known genetic diversity and using allele frequency information associated with heterozygosity and Hardy-Weinberg equilibrium. We worked in 3 variations for the problem. First, we reproduced a previous experiment, but using a multi-objective approach. We found that the smallest set of populations needed to represent all alleles under study was 7, corroborating the results of the previous study, but with more distinct solutions. In the 2nd and 3rd variations, we performed simultaneous optimization of 4 and 5 objectives, respectively. We found similar but refined results for 7 populations, and a larger portfolio considering intra-specific diversity and persistence with populations ranging from 8-22. This is the first study to apply multi-objective algorithms to an SCP problem using alleles at the population level as basic units for analysis.

Phylogenetic eigenvectors and nonstationarity in the evolution of theropod dinosaur skulls.

Despite the long-standing interest in nonstationarity of both phenotypic evolution and diversification rates, only recently have methods been developed to study this property. Here, we propose a methodological expansion of the phylogenetic signal-representation (PSR) curve based on phylogenetic eigenvectors to test for nonstationarity. The PSR curve is built by plotting the coefficients of determination R(2) from phylogenetic eigenvector regression (PVR) models increasing the number of phylogenetic eigenvectors against the accumulated eigenvalues. The PSR curve is linear under a stationary model of trait evolution (i.e. the Brownian motion model). Here we describe the distribution of shifts in the models R(2) and used a randomization procedure to compare observed and simulated shifts along the PSR curve, which allowed detecting nonstationarity in trait evolution. As an applied example, we show that the main evolutionary pattern of variation in the theropod dinosaur skull was nonstationary, with a significant shift in evolutionary rates in derived oviraptorosaurs, an aberrant group of mostly toothless, crested, birdlike theropods. This result is also supported by a recently proposed Bayesian-based method (AUTEUR). A significant deviation between Ceratosaurus and Limusaurus terminal branches was also detected. We purport that our new approach is a valuable tool for evolutionary biologists, owing to its simplicity, flexibility and comprehensiveness.

Geographical genetics of Pseudoplatystoma punctifer (Castelnau, 1855) (Siluriformes, Pimelodidae) in the Amazon Basin.

Geographical genetics allows the evaluation of evolutionary processes underlying genetic variation within and among local populations and forms the basis for establishing more effective strategies for biodiversity conservation at the population level. In this study, we used explicit spatial analyses to investigate molecular genetic variation (estimated using 7 microsatellite markers) of Pseudoplatystoma punctifer, by using samples obtained from 15 localities along the Madeira River and Solimões, Amazon Basin. A high genetic diversity was observed associated with a relatively low FST (0.057; P < 0.001), but pairwise FST values ranged from zero up to 0.21 when some pairs of populations were compared. These FST values have a relatively low correlation with geographic distances (r = 0.343; P = 0.074 by Mantel test), but a Mantel correlogram revealed that close populations (up to 80 km) tended to be more similar than expected by chance (r = 0.360; P = 0.015). The correlogram also showed a exponential-like decrease of genetic similarity with distance, with a patch-size of around 200 km, compatible with isolation-by-distance and analogous processes related to local constraints of dispersal and spatially structured levels of gene flow. The pattern revealed herein has important implications for establishing strategies to maintain genetic diversity in the species, especially considering the threats due to human impacts caused by building large dams in this river system.

Geographical patterns and partition of turnover and richness components of beta-diversity in faunas from Tocantins river valley.

There has been a resurging interest in patterns of ß-diversity, especially by the mechanisms driving broad-scale, continental and global patterns, and how partitioning ß-diversity into richness (or nestedness) and turnover components can be linked with such mechanisms. Here we compared two recent methodologies to find richness and turnover components of ß-diversity, using a large regional scale dataset of mammal, bird, reptiles and amphibian species found in seven regions of Central, North and Northeastern Brazil. As well as a simple comparison of the metrics available, we analyzed spatial patterns (i.e., distance-decay similarity) and the effects of biome type in these components using raw and partial Mantel tests. Our analyses revealed that turnover estimated using Baselga's (2010) approach is slightly higher than the estimate using Carvalho's et al. (2012) approach, but all analyses show consistent spatial patterns in species turnover using both methods. Spatial patterns in ß-diversity revealed by Mantel tests are also consistent with expectations based on differential dispersal abilities. Our results also reinforce that spatial patterns in ß-diversity, mainly in the turnover components expressing faunal differentiation, are determined by a mix or broad scale environmental effects and short distance spatially-structured dispersal.

Geographic shifts in climatically suitable areas and loss of genetic variability in Dipteryx alata ("Baru" Tree; Fabaceae).

Many species are expected to suffer strong shifts in their geographic ranges due to climate changes in the next 50 years, with severe consequences for biodiversity patterns and population structure. We used here an ensemble forecast approach for obtaining species' range in which multiple species distribution models and climatic models were combined to model loss of genetic variability in Baru, Dipteryx alata (Fabaceae), an economically important Neotropical tree native to the Cerrado of Brazil. We estimated a series of genetic parameters (number of alleles per locus, expected heterozygosity under Hardy-Weinberg equilibrium and mutation-drift equilibrium) for this species based on eight microsatellite loci. We then recalculated these parameters assuming that local populations in areas of low future environmental suitability will go extinct. All genetic parameters remained approximately constant up to a 50% threshold of climatic suitability in the future; after this critical threshold there is an abrupt reduction in all parameters, although the magnitude of shift is only about 10% of current values, on average. Thus, despite the shifts in geographic range and climatically suitable areas towards southeastern Brazil, our analyses do not predict a strong loss of genetic diversity in D. alata because of the broad tolerance of this species, which ensures large future ranges, contrasting with other Cerrado species that have been analyzed in a similar manner.

Combining multiple models to predict the geographical distribution of the Baru tree (Dipteryx alata Vogel) in the Brazilian Cerrado.

The Brazilian Cerrado is a biome of great biodiversity, but detailed information about the diversity and distribution of species in this region is still insufficient for both testing ecological hypotheses and for conservation purposes. Among native plants in the Cerrado, Dipteryx alata Vogel (commonly known as the "Baru" tree), has a high potential for exploitation. The aims of this paper were to predict the potential spatial distribution of D. alata in the Brazilian Cerrado utilising five different niche modelling techniques. These techniques usually provide distinct results, so it may be difficult to choose amongst them. To adjust for this uncertainty, we employ an ensemble forecasting approach to predict the spatial distribution of the Baru tree. We accumulated a total of 448 occurrence points and modelled the subsequent predicted occurrences using seven climatic variables. Five different presence-only ecological niche modelling techniques (GARP, Maxent, BIOCLIM, Mahalanobis Distance and Euclidean Distance) were used and the performance of these models was compared using Receiver Operating Characteristics (ROC) and the Area Under the Curve (AUC). All models presented AUC values higher than 0.68, and GARP presented the highest AUC value, whereas Euclidean Distance presented the lowest. The ensemble forecasting approach suggested a high suitability for the occurrence of the Baru tree in the Central-Western region of the Brazilian Cerrado. Our study demonstrated that modelling species distribution using ensemble forecasting can be an important computational tool for better establishing sampling strategies and for improving our biodiversity knowledge to better identify priority areas for conservation. For the Baru tree, we recommend priority actions for conservation in the central region of the Cerrado Biome.

How many studies are necessary to compare niche-based models for geographic distributions? Inductive reasoning may fail at the end.

The use of ecological niche models (ENM) to generate potential geographic distributions of species has rapidly increased in ecology, conservation and evolutionary biology. Many methods are available and the most used are Maximum Entropy Method (MAXENT) and the Genetic Algorithm for Rule Set Production (GARP). Recent studies have shown that MAXENT perform better than GARP. Here we used the statistics methods of ROC - AUC (area under the Receiver Operating Characteristics curve) and bootstrap to evaluate the performance of GARP and MAXENT in generate potential distribution models for 39 species of New World coral snakes. We found that values of AUC for GARP ranged from 0.923 to 0.999, whereas those for MAXENT ranged from 0.877 to 0.999. On the whole, the differences in AUC were very small, but for 10 species GARP outperformed MAXENT. Means and standard deviations for 100 bootstrapped samples with sample sizes ranging from 3 to 30 species did not show any trends towards deviations from a zero difference in AUC values of GARP minus AUC values of MAXENT. Ours results suggest that further studies are still necessary to establish under which circumstances the statistical performance of the methods vary. However, it is also important to consider the possibility that this empirical inductive reasoning may fail in the end, because we almost certainly could not establish all potential scenarios generating variation in the relative performance of models.

Spatial regression techniques for inter-population data: studying the relationships between morphological and environmental variation.

Understanding the importance of environmental dimensions behind the morphological variation among populations has long been a central goal of evolutionary biology. The main objective of this study was to review the spatial regression techniques employed to test the association between morphological and environmental variables. In addition, we show empirically how spatial regression techniques can be used to test the association of cranial form variation among worldwide human populations with a set of ecological variables, taking into account the spatial autocorrelation in data. We suggest that spatial autocorrelation must be studied to explore the spatial structure underlying morphological variation and incorporated in regression models to provide more accurate statistical estimates of the relationships between morphological and ecological variables. Finally, we discuss the statistical properties of these techniques and the underlying reasons for using the spatial approach in population studies.

Phylogenetic inheritance of genetic variability produced by neutral models of evolution.

The amount of genetic variability in species and populations has been mainly related to microevolutionary forces operating in natural populations and the influence of phylogenetic processes for the distribution of genetic variability has been neglected. To investigate how the current genetic variability distribution depends on the genetic variability of ancestral species, we simulated the evolution of heterozygosity on a pre-determined phylogeny under three neutral models of evolution: genetic drift, drift vs mutation and drift vs migration. The distribution of genetic variability resulting from the simulations was used to estimate the phylogenetic signal by the phylogenetic comparative method of autocorrelation. Phylogenetic signal in genetic variability was observed for each of the three models, and its intensity was generally higher and persisted longer when forces of drift, mutation and migration were reduced. The prediction of a phylogenetic signal in genetic variability has consequences for: population genetics, which must consider biological processes acting at the species level influencing the amount and distribution of genetic variability; the macroevolutionary theory, by giving a theoretical basis for species selection by suggesting a heritability of genetic variability between species, and the meta-analyses of genetic variability, which must deal with the non-independence of species. The patterns observed in phylogenetic signal produced by different models of evolution can be used further to compare with data obtained from molecular markers. This is the first study that analyzes the theoretical expectations for the existence of a phylogenetic signal in a population genetic trait.

Optimizing reproducibility evaluation for random amplified polymorphic DNA markers.

The random amplified polymorphic DNA (RAPD) technique is often criticized because it usually shows low levels of repeatability; thus it can generate spurious bands. These problems can be partially overcome by rigid laboratory protocols and by performing repeatability tests. However, because it is expensive and time-consuming to obtain genetic data twice for all individuals, a few randomly chosen individuals are usually selected for a priori repeatability analysis, introducing a potential bias in genetic parameter estimates. We developed a procedure to optimize repeatability analysis based on RAPD data, which was applied to evaluate genetic variability in three local populations of Tibochina papyrus, an endemic Cerrado plant found in elevated rocky fields in Brazil. We used a simulated annealing procedure to select the smallest number of individuals that contain all bands and repeated the analyses only for those bands that were reproduced in these individuals. We compared genetic parameter estimates using HICKORY and POPGENE softwares on an unreduced data set and on data sets in which we eliminated bands based on repeatability of individuals selected by simulated annealing and based on three randomly selected individuals. Genetic parameter estimates were very similar when we used the optimization procedure to reduce the number of bands analyzed, but as expected, selecting only three individuals to evaluate the repeatability of bands produced very different estimates. We conclude that the problems of repeatability attributed to RAPD markers could be due to bias in the selection of loci and primers and not necessarily to the RAPD technique per se.

Autoregressive modelling of species richness in the Brazilian Cerrado.

Spatial autocorrelation is the lack of independence between pairs of observations at given distances within a geographical space, a phenomenon commonly found in ecological data. Taking into account spatial autocorrelation when evaluating problems in geographical ecology, including gradients in species richness, is important to describe both the spatial structure in data and to correct the bias in Type I errors of standard statistical analyses. However, to effectively solve these problems it is necessary to establish the best way to incorporate the spatial structure to be used in the models. In this paper, we applied autoregressive models based on different types of connections and distances between 181 cells covering the Cerrado region of Central Brazil to study the spatial variation in mammal and bird species richness across the biome. Spatial structure was stronger for birds than for mammals, with R(2) values ranging from 0.77 to 0.94 for mammals and from 0.77 to 0.97 for birds, for models based on different definitions of spatial structures. According to the Akaike Information Criterion (AIC), the best autoregressive model was obtained by using the rook connection. In general, these results furnish guidelines for future modelling of species richness patterns in relation to environmental predictors and other variables expressing human occupation in the biome.

Autoregressive modelling of species richness in the Brazilian Cerrado / Modelagem por auto-regressão da riqueza de espécies no Cerrado Brasileiro

Spatial autocorrelation is the lack of independence between pairs of observations at given distances within a geographical space, a phenomenon commonly found in ecological data. Taking into account spatial autocorrelation when evaluating problems in geographical ecology, including gradients in species richness, is important to describe both the spatial structure in data and to correct the bias in Type I errors of standard statistical analyses. However, to effectively solve these problems it is necessary to establish the best way to incorporate the spatial structure to be used in the models. In this paper, we applied autoregressive models based on different types of connections and distances between 181 cells covering the Cerrado region of Central Brazil to study the spatial variation in mammal and bird species richness across the biome. Spatial structure was stronger for birds than for mammals, with R² values ranging from 0.77 to 0.94 for mammals and from 0.77 to 0.97 for birds, for models based on different definitions of spatial structures. According to the Akaike Information Criterion (AIC), the best autoregressive model was obtained by using the rook connection. In general, these results furnish guidelines for future modelling of species richness patterns in relation to environmental predictors and other variables expressing human occupation in the biome.

Autocorrelação espacial é definida como a falta de independência entre pares de observações a uma dada distância geográfica e é um fenômeno muito freqüente em dados ecológicos. É importante levar em consideração os efeitos de autocorrelação espacial em ecologia geográfica, tanto para realizar uma descrição mais detalhada dos dados quanto para corrigir estimativas enviesadas do erro Tipo I das análises estatísticas convencionais. Entretanto, para resolver efetivamente esses problemas, é preciso avaliar a melhor forma de incorporar estruturas espaciais nos modelos. Neste estudo, modelos autoregressivos, baseados em diferentes tipos de conexões e distâncias entre 181 células de uma rede cobrindo a região do Cerrado brasileiro, foram ajustados para avaliar a variação espacial de riqueza de mamíferos e aves dentro do bioma. A estrutura espacial foi ligeiramente mais forte para aves do que para mamíferos, com valores de R² variando entre 0,77 e 0,94 para mamíferos e 0,77 e 0,97 para aves, em modelos baseados em diferentes formas de conexão espacial. Segundo o Critério de Informação Akaike (AIC), o modelo autoregressivo melhor ajustado foi obtido através da conexão "em torre". Em geral, esses resultados fornecem diretrizes para futuras modelagens dos padrões de riqueza de espécies que estão associados a preditores ambientais e/ou a variáveis que expressam a ocupação humana no Cerrado.

Transferability of short tandem repeat markers for two wild Canid species inhabiting the Brazilian Cerrado.

The maned wolf (Chrysocyon brachyurus) and the crab-eating fox (Cerdocyon thous) are two wild-canid species found in the Brazilian Cerrado. We tested cross-amplification and transferability of 29 short tandem repeat primers originally developed for cattle and domestic dogs and cats on 38 individuals of each of these two species, collected in the Emas National Park, which is the largest national park in the Cerrado region. Six of these primers were successfully transferred (CSSM-038, PEZ-05, PEZ-12, LOCO-13, LOCO-15, and PEZ-20); five of which were found to be polymorphic. Genetic parameter values (number of alleles per locus, observed and expected heterozygosities, and fixation indices) were within the expected range reported for canid populations worldwide.

Phylogenetic autocorrelation and evolutionary interpretation of the higher-taxon approach for biodiversity analyses.

Although in most recent broad-scale analyses, diversity is measured by counting the number of species in a given area or spatial unity (species richness), a 'top-down' approach has been used sometimes, counting higher-taxon (genera, family) instead of species with some advantages. However, this higher-taxon approach is quite empirical and the cut-off level is usually arbitrarily defined. In this work, we show that the higher-taxon approach could be theoretically linked with models of phenotypic diversification by means of phylogenetic autocorrelation analysis in such a way that the taxonomic (or phylogenetic) rank to be used could not be necessarily arbitrary. This rank expresses past time in which taxa became independent for a given phenotypic trait or for the evolution of average phenotypes across different traits. We illustrated the approach by evaluating phylogenetic patches for 23 morphological, ecological and behavioural characters in New World terrestrial Carnivora. The higher-taxon counts at 18.8 mya (S(L)) defined by phylogenetic correlograms are highly correlated with species richness (r = 0.899; P < 0.001 with ca. 13 degrees of freedom by taking spatial autocorrelation into account). However, S(L) in North America is usually larger than in South America. Thus, although there are more species in South and Central America, the fast recent diversification that occurred in this region generated species that are "redundant" in relation to lineages that were present at 18.8 my. BP. Therefore, the number of lineages can be comparatively used as a measure of evolutionary diversity under a given model of phenotypic divergence among lower taxonomic units.

Phylogenetic autocorrelation and evolutionary interpretation of the higher-taxon approach for biodiversity analyses / Autocorrelação filogenética e a interpretação evolutiva para análise de número de taxa em análises de biodiversidade

Although in most recent broad-scale analyses, diversity is measured by counting the number of species in a given area or spatial unity (species richness), a `top-down' approach has been used sometimes, counting higher-taxon (genera, family) instead of species with some advantages. However, this higher-taxon approach is quite empirical and the cut-off level is usually arbitrarily defined. In this work, we show that the higher-taxon approach could be theoretically linked with models of phenotypic diversification by means of phylogenetic autocorrelation analysis in such a way that the taxonomic (or phylogenetic) rank to be used could not be necessarily arbitrary. This rank expresses past time in which taxa became independent for a given phenotypic trait or for the evolution of average phenotypes across different traits. We illustrated the approach by evaluating phylogenetic patches for 23 morphological, ecological and behavioural characters in New World terrestrial Carnivora. The higher-taxon counts at 18.8 mya (S L) defined by phylogenetic correlograms are highly correlated with species richness (r = 0.899; P < 0.001 with ca. 13 degrees of freedom by taking spatial autocorrelation into account). However, S L in North America is usually larger than in South America. Thus, although there are more species in South and Central America, the fast recent diversification that occurred in this region generated species that are "redundant" in relation to lineages that were present at 18.8 my. BP. Therefore, the number of lineages can be comparatively used as a measure of evolutionary diversity under a given model of phenotypic divergence among lower taxonomic units.

Embora as análises da biodiversidade em escalas geográficas amplas sejam normalmente realizadas em nível das espécies, alguns trabalhos recentes têm utilizado contagens de categorias taxonômicas mais elevadas, com algumas vantagens. Entretanto, essa abordagem é aplicada de forma empírica e o nível hierárquico escolhido (gênero, famílias, etc.) é geralmente arbitrário. Este trabalho, mostra que essa abordagem pode ser ligada teoricamente aos modelos de evolução fenotípica pelos métodos de autocorrelação filogenética. Esse nível da hierarquia deve expressar o tempo passado no qual os taxa analisados se tornam independentes estatisticamente, para o fenótipo. O método proposto foi aplicado para analisar a evolução fenotípica de 23 caracteres morfológicos, ecológicos e comportamentais em espécies de Carnivora do Novo Mundo. A contagem de linhagens há 18,8 milhões de anos atrás, definida pelos correlogramas filogenéticos, foi altamente correlacionada com a riqueza de espécies (r = 0,899; P < 0,001 com 13 graus de liberdade, levando em consideração a autocorrelação espacial). O número de linhagens foi maior na América do Norte, de modo que embora haja mais espécies na região tropical, estas representam eventos recentes de diversificação, com espécies redundantes em relação às linhagens que existiam há 18,8 milhões de anos atrás. O número de linhagens definido por autocorrelação pode ser utilizado como uma medida de diversidade evolutiva sob um dado modelo de divergência fenotípica.

Priority areas for anuran conservation using biogeographical data: a comparison of greedy, rarity, and simulated annealing algorithms to define reserve networks in cerrado.

Spatial patterns in biodiversity variation at a regional scale are rarely taken into account when a natural reserve is to be established, despite many available methods for determining them. In this paper, we used dimensions of occurrence of 105 species of Anura (Amphibia) in the cerrado region of central Brazil to create a regional system of potential areas that preserves all regional diversity, using three different algorithms to establish reserve networks: "greedy", rarity, and simulated annealing algorithms. These generated networks based on complementarity with 10, 12, and 8 regions, respectively, widely distributed in the biome, and encompassing various Brazilian states. Although the purpose of these algorithms is to find a small number of regions for which all species are represented at least once, the results showed that 67.6%, 76.2%, and 69.5% of the species were represented in two or more regions in the three networks. Simulated annealing produced the smallest network, but it left out three species (one endemic). On the other hand, while the greedy algorithm produce a smaller solution, the rarity-based algorithm ensured that more species were represented more than once, which can be advantageous because it takes into consideration the high levels of habitat loss in the cerrado. Although usually coarse, these macro-scale approaches can provide overall guidelines for conservation and are useful in determining the focus for more local and effective conservation efforts, which is especially important when dealing with a taxonomic group such as anurans, for which quick and drastic population declines have been reported throughout the world.

Priority areas for anuran conservation using biogeographical data: a comparison of greedy, rarity, and simulated annealing algorithms to define reserve networks in Cerrado

Os padrões espaciais da variação da biodiversidade em escalas regionais raramente são considerados na escolha de uma reserva (unidades de conservação), a despeito dos diversos métodos disponíveis para esse fim. Neste trabalho, usamos dados da extensão de ocorrência de 105 espécies de Anura (Amphibia) na região de Cerrado, no Brasil Central, para estabelecer um sistema regional de áreas potenciais que preserve toda a diversidade da região. Para tanto, três algoritmos de seleção de redes de reservas foram testados: "greedy", raridade e "annealing" simulado. Com base na complementação, esses algoritmos geraram redes com 10, 12 e 8 regiões, respectivamente, sendo estas amplamente distribuídas no bioma e contemplando diferentes Estados da União. Esses algoritmos buscam o menor número de regiões que representem todas as espécies pelo menos uma vez. No entanto, 67,6%, 76,2% e 69,5% das espécies foram representadas ("preservadas") em duas ou mais regiões nas três redes de reservas selecionadas pelos métodos citados. O algoritmo "annealing" simulado resultou na menor rede, no entanto, não incluiu áreas para a preservação de três espécies (sendo uma delas endêmica). Por outro lado, embora o algoritmo de "greedy" tenha resultado em menor solução, o método baseado na raridade garante que mais espécies sejam representadas mais de uma vez, o que pode ser vantajoso considerando a elevada taxa de perda de habitat no Cerrado. Embora imprecisas, as abordagens em grandes escalas espaciais podem indicar estratégias gerais para a conservação e definir esforços de conservação locais e mais efetivos. Isto é especialmente importante quando se trata de um grupo taxonômico como os anuros, com declínios populacionais acentuados registrados mundialmente.

Macroecological analyses support an overkill scenario for late Pleistocene extinctions.

The extinction of megafauna at the end of Pleistocene has been traditionally explained by environmental changes or overexploitation by human hunting (overkill). Despite difficulties in choosing between these alternative (and not mutually exclusive) scenarios, the plausibility of the overkill hypothesis can be established by ecological models of predator-prey interactions. In this paper, I have developed a macroecological model for the overkill hypothesis, in which prey population dynamic parameters, including abundance, geographic extent, and food supply for hunters, were derived from empirical allometric relationships with body mass. The last output correctly predicts the final destiny (survival or extinction) for 73% of the species considered, a value only slightly smaller than those obtained by more complex models based on detailed archaeological and ecological data for each species. This illustrates the high selectivity of Pleistocene extinction in relation to body mass and confers more plausibility on the overkill scenario.

Worldwide patterns in species richness of Falconiformes: analytical null models, geometric constraints, and the mid-domain effect.

Recently, the hypothesis that the geographic distribution of species could be influenced by the shape of the domain edges, the so-called Mid-Domain Effect (MDE), has been included as one of the five credible hypotheses for explaining spatial gradients in species richness, despite all the unsuccessful current attempts to prove empirically the validity of MDE. We used data on spatial worldwide distributions of Falconiformes to evaluate the validity of MDE assumptions, incorporated into two different sorts of null models at a global level and separately across five domains/landmasses. Species richness values predicted by the null models of the MDE and those values predicted by Net Primary Productivity, a surrogate variable expressing the effect of available energy, were compared in order to evaluate which hypothesis better predicts the observed values. Our tests showed that MDE continues to lack empirical support, regardless of its current acceptability, and so, does not deserve to be classified as one possible explanation of species richness gradients.